class_docstr: Method that greedily adds sentences to a summary so long as it decreases the
  KL Divergence.
  Source: http://www.aclweb.org/anthology/N09-1041
class_docstr_tok: ["Method","that","greedily","adds","sentences","to","a","summary","so","long","as","it","decreases","the","KL","Divergence",".","Source",":","http",":","\/\/www.aclweb.org\/anthology\/N09-1041"]
docstr: Computes the normalized term frequency as explained in http://www.tfidf.com/
  
  :type sentences: [sumy.models.dom.Sentence]
docstr_tok: ["Computes","the","normalized","term","frequency","as","explained","in","http",":","\/\/www.tfidf.com\/",":","type","sentences",":","[","sumy.models.dom.Sentence","]"]
code: def compute_tf(self, sentences):
      """
      Computes the normalized term frequency as explained in http://www.tfidf.com/
  
      :type sentences: [sumy.models.dom.Sentence]
      """
      content_words = self._get_all_content_words_in_doc(sentences)
      content_words_count = len(content_words)
      content_words_freq = self._compute_word_freq(content_words)
      content_word_tf = dict(
          (w, f / content_words_count)
          for w, f in content_words_freq.items()
      )
      return content_word_tf
  
file_path: sumy/sumy/summarizers/kl.py
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  import math
  from ._summarizer import AbstractSummarizer
label_desc: Use image node_id 8 for calling the KLSummarizer obj's underlying member method code with example usage: obj.compute_tf(sentences) and returns: content_word_tf